Implementation of Web Page Prediction Using Web Usage Mining by Markov Tree Algorithm and Longest Common Subsequence (LCS)

Abstract

A web prediction model helps to predict user requests ahead of time, making web servers more responsive. Web usage mining based on users’ clickstream data and it is the main subject in web prediction systems. Prediction the near future web pages based on user’s current clickstream data. This paper presents web page prediction through web usage mining and it also presents classification of users’ navigation pattern to predict users’ future intentions. Markov Tree algorithm is used in web access pattern generation. Markov tree model behaves an All-Kth-order Markov model because of its ability to recognize different order models according to the height of the tree. A Markov tree gives a complete description on the frequency with which a particular state occurs, and the number of times a path to a particular state is used, to access its child nodes. Longest Common Subsequence algorithm is used in web page prediction based on user access patterns.